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Debris flow is a natural hazard typically triggered by heavy rainfall. Previous research aimed at forecasting the occurrence of debris flows have led to the development of several rainfall duration-intensity thresholds for different areas using the second-percentile method that allows a missed-alarm probability of up to 2%, while disregarding the occurrence of false alarms. The current study aims to develop rainfall duration-intensity thresholds for debris flow forecasting taking into account both missed alarms and false alarms. Specifically, the new optimization approach seeks to determine the optimal duration-intensity threshold associated with the lowest missed- and false-alarm probabilities combined. In addition to the methodology, a case study is presented to show that the new optimization approach is feasible for determining rainfall duration-intensity thresholds in debris flow forecasting, and is more efficient than the method currently in use, which is associated with a higher probability of missed and false alarms combined.

Characterizing the standard deviation of soil properties is important to a geotechnical probabilistic analysis, and the task is usually achieved with sufficient samples. However, sometimes soil samples or soil tests in a project could be limited (e.g., only one sample), making classical statistics approaches less applicable to the estimating. In this technical note, we introduce a new Bayesian algorithm to estimate the standard deviation of soil properties, using limited project-specific samples along with relevant prior information from the literature. In addition to the methodology, a few demonstrations are also given in the paper, to re-evaluate the standard deviation of soil properties with the new algorithm. Like many Bayesian algorithms, the new application could be useful for site characterizations when samples are limited.

Engineering risk assessment is to estimate the structure’s failure probability multiplied by its failure consequences. On the other hand, the analysis was sometimes performed on a more general basis, utilizing a few indicators to quantify relative risk levels for decision-making. On the basis of such a framework, this paper introduces a novel risk assessment on 18 active faults in Taiwan, considering the fault’s location, earthquake size and return period from the literature. The result shows that the Chelungpu Fault in central Taiwan has the highest risk score among the 18 active faults, in contrast to the Hengchun Fault in southern Taiwan which has the lowest risk. Besides this, the 18 active faults in Taiwan were classified into four groups based on this risk assessment, and the classification could help the region’s sustainable development against earthquake hazard.

The region around Taiwan is known for active seismicity, and a few studies have reported a high seismic hazard in this region, including a deterministic seismic hazard analysis (DSHA) study. Essentially, DSHA is to estimate earthquake ground motions considering the worst-case earthquake size and location, but without considering the seismic hazards from non-controlling sources. Understandably, when many non-controlling sources are present, the original DSHA framework could be insufficient. Therefore, using the extreme probability theory, this study introduces a new DSHA framework taking non-controlling seismic sources into account during DSHA calculations. The new method was applied to a seismic hazard assessment for Taiwan, showing that near the conjunctions of seismic source zones, the increase in seismic hazard could be substantial after considering a total of 19 non-controlling sources. More importantly, like other seismic hazard assessments for Taiwan, this study conveys the same alarming message that a high level of seismic hazard should be present around the region.

According to the Central Geological Survey Taiwan (CGST), the Meishan fault in Central Taiwan, which induced a catastrophic earthquake in 1906, is considered capable of triggering equivalent events with a return period of 162 years. Therefore, as the next event is expected around 2070, the Meishan fault poses a high level of earthquake risk in Central Taiwan, especially for those cities and townships very close to the fault. However, the best-estimate return period (162 years) and earthquake magnitude (7.1 M L) reported by the CGST must be subject to some uncertainty, because such an event is very unlikely to recur every 162 years. Therefore, this study carried out a series of seismic hazard assessments for three major cities close to the Meishan fault, with the uncertainty of the best-estimate information being determined using the Rosenblueth algorithm. The results show that for Chaiyi city, which the Meishan fault passes through, the probability of the current design value (i.e., PGA = 0.33 g) being exceeded by the earthquake motion induced by the Meishan fault in the next 50 years would be as high as 55 %. Therefore, further studies should be carried out to obtain a better understanding of the Meishan fault, to develop a robust hazard mitigation plan for nearby cities.